Method and apparatus for distributing satellite tracking information

ABSTRACT

A method and apparatus for distributing satellite tracking data to a remote receiver. At least a portion of the satellite tracking data is extracted from memory and is formatted into a format prescribed by a remote receiver. The formatted data is transmitted to the remote receiver via a distribution network.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 09/875,809, filed Jun. 6, 2001 which is herein incorporated byreference in its entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to generating satellite trackinginformation for earth orbiting satellites. More specifically, theinvention relates to a method and apparatus for generating anddistributing satellite tracking information through a network orcommunications link.

2. Description of the Related Art

A positioning receiver for the Global Positioning System (GPS) usesmeasurements from several satellites to compute a position. The processof acquiring the GPS radio signal is enhanced in speed and sensitivityif the GPS receiver has prior access to a model of the satellite orbitand clock. This model is broadcast by the GPS satellites and is known asan ephemeris or ephemeris information. Each satellite broadcasts its ownephemeris once every 30 seconds. Once the GPS radio signal has beenacquired, the process of computing position requires the use of theephemeris information.

The broadcast ephemeris information is encoded in a 900 bit messagewithin the GPS satellite signal. It is transmitted at a rate of 50 bitsper second, taking 18 seconds in all for a complete ephemeristransmission. The broadcast ephemeris information is typically valid for2 to 4 hours into the future (from the time of broadcast). Before theend of the period of validity the GPS receiver must obtain a freshbroadcast ephemeris to continue operating correctly and produce anaccurate position. It is always slow (no faster than 18 seconds),frequently difficult, and sometimes impossible (in environments withvery low signal strengths), for a GPS receiver to download an ephemerisfrom a satellite. For these reasons it has long been known that it isadvantageous to send the ephemeris to a GPS receiver by some other meansin lieu of awaiting the transmission from the satellite. U.S. Pat. No.4,445,118, issued Apr. 24, 1984, describes a technique that collectsephemeris information at a GPS reference station, and transmits theephemeris to the remote GPS receiver via a wireless transmission. Thistechnique of providing the ephemeris, or equivalent data, to a GPSreceiver has become known as “Assisted-GPS”. Since the source ofephemeris in Assisted-GPS is the satellite signal, the ephemerisinformation remains valid for only a few hours. As such, the remote GPSreceiver must periodically connect to a source of ephemeris informationwhether that information is received directly from the satellite or froma wireless transmission. Without such a periodic update, the remote GPSreceiver will not accurately determine position.

The deficiency of the current art is that there is no source ofsatellite trajectory and clock information that is valid for longer thana few hours into the future, and it can be expensive to send theephemeris information repeatedly to the many remote devices that mayneed it. Moreover, mobile devices may be out of contact from the sourceof the Assisted-GPS information when their current ephemeris becomesinvalid.

Therefore, there is a need in the art for a method and apparatus forproviding satellite trajectory and clock information that is valid foran extended period into the future, e.g., many days into the future.

SUMMARY OF THE INVENTION

The present invention is a method and apparatus for generating satellitetracking data (STD) that is valid for extend periods of time into thefuture, i.e., long term STD or LT-STD. The STD may contain futuresatellite trajectory information and/or satellite clock information. TheSTD is derived by receiving at one or more satellite tracking stationsthe signals from at least one satellite and determining satellitetracking information (STI) from the received signals. STI containspresent satellite orbit trajectory data and satellite clock information.

The STD may be provided to a remote satellite signal receiver via anetwork or communications system. The satellite system may include theglobal positioning system (GPS), GLONASS, GALILEO, or other satellitesystems that may use STD to enhance the performance of the receiver. Byusing the LT-STD, a remote receiver may accurately operate for dayswithout receiving an update of the broadcast ephemeris information asnormally provided from the satellites.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the above recited features of the presentinvention are attained and can be understood in detail, a moreparticular description of the invention, briefly summarized above, maybe had by reference to the embodiments thereof which are illustrated inthe appended drawings.

It is to be noted, however, that the appended drawings illustrate onlytypical embodiments of this invention and are therefore not to beconsidered limiting of its scope, for the invention may admit to otherequally effective embodiments.

FIG. 1 depicts a system for creating and distributing satellite trackingdata (STD) to remote GPS receivers;

FIG. 2 depicts a method for forming the STD from the satellitemeasurements made at satellite tracking stations;

FIG. 3 depicts a timeline of STD data that conforms to the broadcastephemeris format models as described in ICD-GPS-200C yet spans manyhours;

FIG. 4 depicts a flow diagram of a method that uses a least squaresestimation technique to update parameters in an orbit trajectory model;

FIG. 5 depicts the error in the orbit model derived from the STD, andcompares the error to the error in the broadcast ephemeris;

FIG. 6 depicts an example of a data table that could be used in an STDdatabase.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 1 depicts a block diagram of a system 100 for creating anddistributing satellite tracking data (STD). The satellite system mayinclude the global positioning system (GPS), GLONASS, GALILEO, or othersatellite systems that may use STD to enhance the performance of thereceiver. The following disclosure uses GPS as an illustrative systemwithin which the invention operates. From the following disclosure,those skilled in the art will be able to practice the invention inconjunction with other satellite systems.

A network of GPS tracking stations 102 is used to collect measurementdata from the GPS satellites 104. Such a network is described in detailin U.S. patent application Ser. No. 09/615,105, filed Jul. 13, 2000. Thenetwork could comprise several tracking stations that collect satellitetracking information (STI) from all the satellites in the constellation,or a few tracking stations, or a single tracking station that onlycollects STI for a particular region of the world. An STD collection andcomputation server 106 collects and processes the measurement data (thismeasurement data is referred to herein as satellite tracking information(STI) that includes at least one of: code phase measurements, carrierphase measurements, Doppler measurements, or ephemeris data). In thepreferred embodiment, measurement data is obtained from both the L1 andL2 frequencies on which the GPS satellites transmit. Alternativeembodiments may use only one of these frequencies, and/or otherfrequencies used by other satellite systems or by future versions of theGPS system. The server 106 produces: 1) accurate satellite tracking data(STD) (e.g., a trajectory of each satellite and/or a clock offsetmeasurement) during the data collection period, 2) a prediction of thefuture STD of each satellite, and 3) models that match the future STD ofeach satellite. The server 106 comprises a central processing unit (CPU)118, support circuits 122, and memory 120. The CPU 118 may be any one ofthe many CPUs available on the market to perform general computing.Alternatively, the CPU may be a specific purpose processor such as anapplication specific integrated circuit (ASIC) that is designed toprocess satellite tracking information. The support circuits 122 arewell known circuits such as clock circuits, cache, power supplies andthe like. The memory 120 may be read only memory, random access memory,disk drive storage, removable storage or any combination thereof. Thememory 120 stores executable software, e.g., LT-STD software 124, that,when executed by the CPU 118, causes the system 100 to operate inaccordance with the present invention.

The set of satellite trajectory and clock data produced by the LT-STDsoftware 124 constitutes the STD information, and is stored in an STDdatabase 108. A distribution server 110 accesses the database 108 togather the most recent set of data, formats the data using thetrajectory conversion software 111 according to the relevant interfacestandard, and distributes the formatted data to GPS devices 112 thatrequire satellite orbit information. The distribution process may be bysome form of wireless communications system 114, or over the Internet116, or a combination of both, or by some other means of communication.Once the GPS devices 112 have received the orbit data, they may operatecontinually for many days without needing to download fresh broadcastephemeris from the satellites or from any other source. The orbit datadistributed to the GPS devices may be in the same format as thebroadcast ephemeris or may be some other model format that is defined bythe GPS device. Herein this orbit data is generally referred to as asatellite tracking model (STM). The loading of the STM into the GPSreceiver can be accomplished in many ways. Using the cradle for apersonal digital assistant (PDA), direct connection to a network, or awireless technology, such as Bluetooth or a cellular network, are a fewexamples of how the ephemeris data can be transferred to the receiver.The transmission is generally accomplished by broadcasting the LT-STD(or a model representing all or a portion of the LT-STD) withoutknowledge of the specific location of the GPS receiver. As such, thedistribution server does not require the GPS receiver to send anyinformation through the network to the distribution server.

Since GPS is a ranging system in and of itself, the data transmitted bythe GPS satellites can be used to determine the range, range-rate andclock offsets to the GPS satellites from a set of tracking stations.This set of observations generated by the tracking stations 102 is usedin the orbit determination process, and in the estimation of thesatellite clock characteristics. The set of monitoring stations 102could be a single station, a public network such as the ContinuouslyOperating Reference System (CORS), or a privately owned and/or operatednetwork.

FIG. 2 illustrates the preferred embodiment of a process for computingLT-STD. The process begins at step 202 with the collection of satellitemeasurements from the network of tracking stations. Measurements such ascode phase, (CP), carrier phase (CPH), and Doppler may be used for GPSsatellite tracking information. At step 204, the measurements are usedto compute the satellite trajectories and clock offsets over the periodsduring which the data was collected. This step is performed usingstandard GPS processing techniques and software packages well known inthe art. Examples of this type of software are GIPSY from the JetPropulsion Laboratory (JPL), GEODYN from NASA Goddard Space FlightCenter (GSFC), and the commercial product, MicroCosm, from Van MartinSystems.

At step 206, the satellite trajectories and clock offsets from step 204are propagated into the future with the same software package, usingstandard orbit models, such as gravity, drag, solar radiation pressure,tides, third body effects, precession, nutation, and other conservativeand non-conservative forces effecting the satellite trajectory. Theseare normally the same force models that are used in the estimation ofthe satellite orbits during the data fit interval. A subset of thesemodels, such as those for drag and solar radiation pressure, areadjusted during the orbit estimation process described in step 204 tobest fit the trajectory. This combination of known and estimated forcemodels parameters is used in the propagation 206 to provide thepropagated orbit for time outside the data fit interval. The clockoffsets for GPS satellites are typically very small, and change linearlyover time. These clock offsets are propagated into the future usingstandard models, such as a second order model containing clock offset,drift, and drift rate.

At step 208, the propagated satellite trajectories and/or clock offsetsare stored as STD in a database. At step 210, the trajectory conversionsoftware converts the LT-STD data into a model and format expected bythe GPS device to which the model is to be provided. At step 212, theprescribed model or information is output. For use with existing GPSreceivers, the preferred embodiment of the model is the GPS ephemerismodel as described in ICD-GPS-200 and an ephemeris model is generatedfrom the LT-STD for each 4 hour period as illustrated in the timeline300 of FIG. 3, i.e., a different model 301, 302 and so on is generatedfor each six hour period. As such, the plurality of models 301, 302 andso on cumulatively span the lenght of the available LT-STD.

In an alternate embodiment, at step 204, the satellite trajectories andclock offsets may be estimated using the data broadcast by thesatellites and the standard equations given in ICD-GPS-200c.

The orbit model is a mathematical representation of the satellitetrajectory that describes the trajectory as a function of a small numberof variables and eliminates the need to provide satellite positionvectors explicitly as a table of time vs. satellite positions. Anexample of an ephemeris model is the classic six element Keplerianorbital model. Although this model lacks long term accuracy, it is afunctional ephemeris model for providing satellite trajectoryinformation as a function of a small number of variables. In thepreferred embodiment, the model used to describe the trajectory is GPSstandard ephemeris, specified in ICD-GPS-200c, following the sameconventions and units. This is the preferred method to provide maximumcompatibility with existing GPS receivers. However, other orbit modelscould also be used to represent the satellite trajectory. Orbit modelscan be selected to provide increased accuracy, longer duration fits,more compact representation of the trajectory, or other optimizationsrequired in an application.

This invention is different from the current art in that the orbit modelprovided to the GPS device is not the ephemeris data broadcast by theGPS satellites. Current art downloads the ephemeris broadcast from theGPS satellites and retransmits that data to GPS devices. In thisinvention, the broadcast ephemeris data is not required at any stage andis not used in the preferred implementation.

The broadcast ephemeris data provided by the GPS satellites cover aspecific time period (typically 4 hours) and the end of that time theinformation becomes unusable. For example, if a device receives abroadcast ephemeris that will expire in 5 minutes, the device would needthe new broadcast ephemeris before operating outside that 5 minuteinterval. With this invention, the STD may be formatted for the timeperiod required by the device. This time period may be for the currenttime forward or may be for some time interval in the future. Forexample, a device may request orbit information in the standard GPSephemeris format for the current time. In this case, the ephemerisprovided to the device would be valid for the next 6 hours. The devicecould request orbit information for the next 12 hours in the standardGPS format which could be supplied as two six hour ephemeris orbitmodels. In addition, different orbit models and formats that supportdifferent accuracies and standards can be generated from the LT-STD.

Fitting the LT-STD to the desired orbit model can be accomplished in anumber of mathematical methods. The preferred embodiment is aleast-squares fit of the orbit model parameters to the trajectory data.Other methods, such as Kalman filters or other estimators can also beused to obtain the orbit model parameters that best fit the trajectorydata. These techniques of fitting data to orbit models are well known topeople skilled in the art of orbit determination and orbit modeling.

The least squares technique provides an optimal fit of the trajectorydata to the orbit model parameters. FIG. 4 depicts a flow diagram of amethod of generating an orbit model using a least squares estimationtechnique. One embodiment of LT-STD is a table representation of time,position, and clock offset for each satellite, as shown in FIG. 6. Thetime, position, and clock offset can be in any time/coordinate system.For the purpose of simplicity and illustration, the time/coordinatesystem is GPS time and Earth-Centered-Earth-Fixed (ECEF) position in theWorld Geodetic Survey 1984 (WGS-84) reference frame.

At step 402, the STD for the desired time interval is extracted from theSTD database. The orbit model parameters are initialized to the orbitmodel values obtained by a similar process for the previous interval.This guarantees that the initial orbit model parameters are a good fitat least for the beginning of the desired time interval. The rest of theprocess 400 will ensure that the parameters are adjusted so that theybecome a good fit for the entire time interval.

In the preferred embodiment there are 15 orbital parameters to beadjusted:

Square root of semi-major axis (meters{circumflex over ( )}½)

Eccentricity (dimensionless)

Amplitude of sine harmonic correction term to the orbit radius (meters)

Amplitude of cosine harmonic correction term to the orbit radius(meters)

Mean motion difference from computed value (radians/sec)

Mean anomaly at reference time (radians)

Amplitude of cosine harmonic correction term to the argument of latitude(radians)

Amplitude of sine harmonic correction term to the argument of latitude(radians)

Amplitude of cosine harmonic correction term to the angle of inclination(radians)

Amplitude of sine harmonic correction term to the angle of inclination(radians)

Longitude of ascending node of orbit plane at weekly epoch (radians)

Inclination angle at reference time (radians)

Rate of inclination angle (radians/sec)

Argument of perigee (radians)

Rate of right ascension (radians/sec)

Although it will be readily apparent that more terms may be used, forbetter fits, or, fewer terms may be used for a more compact model.

At step 404, the orbit model is used to predict what the trajectorywould be, the predicted data is denoted the “Model Trajectory Data”(MTD). If the model were perfect, the MTD would coincide exactly withthe STD. At step 406, the MTD and OTD are compared to see how closelythe orbit model fits the orbit data. In the preferred embodiment, thecomparison step 406 is performed by summing the squares of thedifferences between each trajectory point in the OTD and thecorresponding point in the MTD, and comparing the resulting sum to athreshold. If the fit is “good”, the model parameters are deemed “good”and the process stops at step 410. If the fit is not good then the modelparameters are adjusted at step 408. There are many techniques wellknown in the art for adjusting model parameters to fit data. Forexample, in FIG. 5, the six-hour ephemeris model was adjusted to fit sixhours of OTD using a subspace trust region method based on theinterior-reflective Newton method described in Coleman, T. F., and Y.Li, “On the convergence of reflective Newton methods for large scalenonlinear minimization subject to bounds”, Mathematical Programming,Vol. 67, Number 2, pp. 189-224, 1994, and Coleman, T. F., and Y. Li, “Aninterior, trust region approach for nonlinear minimization subject tobounds”, SIAM Journal on Optimization, Vol. 6, pp. 418-445, 1996. Thereare standard computer packages, e.g., MATLAB Optimization Toolbox, thatmay be used to implement these methods.

Steps 404, 406 and 408 are repeated until the model parameters are foundthat fit the OTD well.

When fitting an orbit model to trajectory data, there are many choicesof which orbit model to choose. The preferred embodiment is to use orbitmodels with parameters that have been defined in well-known standards.In one embodiment, the ephemeris parameters defined in the GPS interfacecontrol document, ICD-GPS200c, are used. The ICD-GPS-200c definitionincludes a bit that specifies a 4-hour fit or a 6-hour fit. Typically,the satellite data is broadcast in 4-hour fits and, by the time thisdata is obtained by the observer of the satellite, the data is oftennear the end of its fit interval. In one embodiment of the currentinvention, sequential 6 hour windows of STD are used to create 6-hourephemeris models, using the technique described in FIG. 4 and theaccompanying text. This produces a set of ephemeris models asillustrated in FIG. 3. Although these particular 6-hour models are notavailable without this invention, the models nonetheless are definedusing standard parameters (i.e. ICD-GPS-200c) and will be understood byany device that was designed to be compatible with said standard.

Alternatively, the transmission time for the model may be dynamicallydetermined in response to various transmission network characteristics,e.g., cellular telephone rate structures, data transmission bandwidths,low network utilization periods, low network congestion periods and thelike. Thus, the invention determines present value of the specificcharacteristics and compares the present value to a threshold. Inresponse to the comparison, the invention will transmit or not transmitthe model. For example, the invention may monitor the network trafficand determine the least congested time to transmit the model. Manywireless networks have time varying rates. For example, cellulartelephone use is often less expensive on weekends compared to mid-weekrates. A useful embodiment of the current invention is to create asatellite tracking model that is valid for the period betweeninexpensive rates (example: valid from one Saturday to the next), andtransmit the model during the time that the rate is inexpensive. Assuch, the model is transmitted for less cost than if the models weretransmitted during a peak rate period. Also, or as an alternative, onemay define and send the model to coincide with periods of low data useon the network—whether the network is wireless or not (e.g. theinternet). Those skilled in the art will realize that many othertransmission time optimization characteristics can be used to determinewhen it is best to transmit the model to the receiver(s).

FIG. 5 shows an example of Satellite Tracking Data (STD) that wasgenerated for a time interval of greater than six hours. Then, using thetechnique described by FIG. 4 and accompanying text, parameters of anICD-GPS-200c ephemeris model were adjusted to give a best fit to 6 hoursof the STD. The orbit modeled by this 6-hour ephemeris was then comparedto the true trajectory and, for comparison, the true trajectory was alsocompared to the orbit modeled by the broadcast ephemeris. The resultsare shown in FIG. 5, illustrating how the broadcast ephemeris losesvalidity while the ephemeris created by this invention maintains itsvalidity with approximately one meter of error.

The clock offset of GPS satellites is easily modeled by threeparameters. In the preferred embodiment, the measured clock offset ismodeled by the three parameters defined in ICD-GPS-200c. Theseparameters represent clock offset, drift, and drift rate. The parametersare adjusted in a similar way to the method 400 described above to givea model that best fits the measured data over the time interval.

Alternative embodiments may use longer fit intervals, such as 8, 14, 26,50, 74, 98, 122, or 146 hours for each ephemeris model. These fitintervals are envisaged in ICD-GPS-200c, but are seldom, if ever,available from the broadcast ephemeris. Under the current invention,models with these fit intervals may be generated even when the broadcastephemeris is limited to a 4-hour fit interval.

Alternative embodiments of the STD data may include observed satellitevelocity, acceleration, clock drift, or clock drift rate and these termsmay be used in the process of fitting a model in ways which are wellknown in the art.

Another embodiment of an orbit model uses the spare data bits in thecurrent ephemeris format of a conventional GPS signal to provideadditional model parameters that would improve the data fit over longtime intervals. For example, subframe 1 has 87 spare bits that areavailable for additional parameters. This technique allows for moreparameters to describe the orbital motion of the satellites withoutcompromising the standard data format. This new ephemeris model is basedon the current ephemeris model with additional correction terms used toaugment the model to support the longer fit intervals with greateraccuracy.

Yet another embodiment of an orbit model is to develop a new set oforbital parameters that describe the satellite orbit which aredifferent, in part or in their entirety, from the GPS ephemeris modelparameters. With the goal of making the fit interval longer, differentparameters may provide a better description of the satellite orbit. Thisnew set of parameters could be defined such that they would fit into theexisting data structures, however, their implementation and algorithmsfor use would be different.

Still a further embodiment of an orbit model would be to develop a newset of orbital parameters that would not fit into the existing GPSephemeris model format. This new set of parameters would be developed tobetter address the trade-off between the number of parameters required,the fit interval, and the orbit accuracy resulting from the model. Anexample of this type of ephemeris parameter set is Brouwer's theory thatcould be used as is or modified to account for GPS specific terms.Brouwer's theory as described in Brouwer, D. “Solution of the Problem ofArtificial Satellite Theory without Drag”, Astron J. 64: 378-397,November 1959 is limited to satellites in nearly circular orbits such asGPS satellites.

Another embodiment is to use a subset of the standard ephemerisparameters defined in ICD-GPS-200c. This approach is particularly usefulwhen bandwidth and/or packet size is limited in the communication linkthat will be used to convey the orbit model to the Remote GPS Receiver.In one such embodiment, the fifteen orbit parameters described above,and in ICD-GPS-200c, may be reduced to a subset of 9 parameters, bysetting all harmonic terms in the model to zero:

Square root of semi-major axis (meters{circumflex over ( )}½)

Eccentricity (dimensionless)

Mean motion difference from computed value (radians/sec)

Mean anomaly at reference time (radians)

Longitude of ascending node of orbit plane at weekly epoch (radians)

Inclination angle at reference time (radians)

Rate of inclination angle (radians/sec)

Argument of perigee (radians)

Rate of right ascension (radians/sec)

Process 400 is then executed using this subset of parameters. Thisreduces the amount of data that must be sent to the Remote GPS Receiver.The receiver can then reconstruct a standard ephemeris model by settingthe “missing” harmonic terms to zero. There are a large number ofalternative embodiments to reduce the size of the data, while stillproviding a model that fits the STD, including:

Removing parameters from the model, and replacing them with a constant,such as zero—as done above—or some other predetermined value, which iseither stored in the Remote GPS Receiver, or occasionally sent to thereceiver.

The resolution of the parameters may be restricted in the process 400,this too reduces the amount of data that must be sent to the mobile GPSreceiver.

Parameters, which are similar among two or more satellites, may berepresented as a master value plus a delta, where the delta requiresfewer bits to encode; an example of this is the parameter Eccentricity,which changes very little among different GPS satellites.

Some of these approaches reduce the ability of the model to fit the dataover a period of time (e.g., six hours). In this case, the fit intervalmay be reduced (e.g. to four hours) to compensate.

While the foregoing is directed to the preferred embodiment of thepresent invention, other and further embodiments of the invention may bedevised without departing from the basic scope thereof, and the scopethereof is determined by the claims that follow.

What is claimed is:
 1. A method for distributing long term satellitetracking data to a remote receiver comprising: extracting at least aportion of long term satellite tracking data from a memory; representingthe at least a portion of long term satellite tracking data in a formatsupported by the remote receiver; and transmitting the formatted data tothe remote receiver.
 2. The method of claim 1 wherein said long termsatellite tracking data 0comprises at least one of: a plurality ofsatellite positions with respect to time for a period of time into thefuture, a plurality of satellite clock offsets with rasped to time for aperiod of time into the future.
 3. The method of claim 1 wherein saidlong term satellite tracking data comprises at least one of: datarepresentative of satellite positions, velocities or acceleration; datarepresentative of satellite clock offsets, drift, or drift rates.
 4. Themethod of claim 1 wherein said format comprises a format that isprescribed by said remote receiver.
 5. The method of claim 1 whereinsaid format is a model containing at least one of: orbital parametersand clock parameters.
 6. The method of claim 5 wherein said orbitalparameters and clock parameters are defined by the global positioningsystem standard.
 7. The method of claim 5 wherein said model comprisesmore than one sequential model, each sequential model being valid for aperiod of time.
 8. The method of claim 5 wherein said model is valid fora period of four hours.
 9. The method of claim 5 wherein said model isvalid for a period of more than four hours.
 10. The method of claim 1wherein said remote receiver is a GPS receiver.
 11. The method of claim1 wherein said remote receiver is a satellite positioning systemreceiver.
 12. The method of claim 1 wherein said format is a standardformat for transmitting satellite models to a global positioning systemreceiver.
 13. The method of claim 1 wherein the long term satellitetracking data is valid for a first period of time and the at least aportion of said long term satellite tracking data is valid for a secondperiod of time, where said first period is longer than said secondperiod.
 14. The method of claim 1 wherein said transmitting step furthercomprises: transmitting using a wireless communications link.
 15. Themethod of claim 14 wherein said transmitting step further comprises:broadcasting the formatted data to a remote receiver.
 16. The method ofclaim 1 wherein said transmitting step comprises: transmitting using acomputer network.
 17. The method of claim 16 wherein said transmittingstep further comprises: broadcasting the formatted data to a remotereceiver.
 18. The method of claim 1 wherein said transmitting stepcomprises: transmitting using the Internet.
 19. The method of claim 18wherein said transmitting step further comprises: broadcasting theformatted data to a remote receiver.
 20. The method of claim 18 whereinsaid transmitting step couples the formatted data to the remote receiverwhen said remote receiver connects to the internet.
 21. The method ofclaim 1, wherein said transmitting step further comprises: determining atime when the cost of transmitting the formatted data is relatively low;and transmitting the formatted data at said time.
 22. The method ofclaim 1, wherein said transmitting step further comprises: determining atime when the congestion of a transmission network is relatively low;transmitting the formatted data at said time.
 23. A method ofdistributing long term satellite tracking data to a remote receiver,using the Internet, comprising: collecting said long term satellitetracking information at a tracking station; processing the long termsatellite tracking information to form satellite tracking data;formatting at least a portion of the long term satellite tracking datainto formatted data that is prescribed by a requirement of the remotereceiver; and sending said formatted data to the remote receiver. 24.The method of claim 23 where said long term satellite trackinginformation data is from at least one OPS satellite.
 25. The method ofclaim 24 where said long term satellite tracking information is at leasta portion of the broadcast ephemeris data from the at least one GPSsatellite.
 26. The method of claim 23 wherein said sending step furthercomprises: broadcasting the formatted data to a remote receiver. 27.Apparatus for distributing long term satellite tracking data to a remotereceiver comprising: a computer for accessing at least a portion of longterm satellite tracking data from a memory and formatting the at least aportion of long term satellite tracking data in a format supported bythe remote receiver; and means for transmitting the formatted data tothe remote receiver.
 28. The apparatus of claim 27 wherein said long tensatellite tracking data comprises at least one of: a plurality ofsatellite positions with respect to time for a period of time into thefuture, a plurality of satellite clock offsets with respect to time fora period of time into the future.
 29. The apparatus of claim 27 whereinsaid long term satellite tracking data comprises at least one of: datarepresentative of satellite positions, velocities or acceleration; datarepresentative of satellite clock offsets, drift, or drift rates. 30.The apparatus of claim 27 wherein said format comprises a format that isprescribed by said remote receiver.
 31. The apparatus of claim 27wherein said format is a model containing at least one of: orbitalparameters and clock parameters.
 32. The apparatus of claim 31 whereinsaid orbital parameters and clock parameters are defined by the globalpositioning system standard.
 33. The apparatus of claim 31 wherein saidmodel comprises more than one sequential model, each sequential modelbeing valid for a period of time.
 34. The apparatus of claim 31 whereinsaid model is valid for a period of more than four hours.
 35. Theapparatus of claim 27 wherein said remote receiver is a GPS receiver.36. The apparatus of claim 27 wherein said remote receiver is asatellite positioning system receiver.
 37. The apparatus of claim 27wherein said format is a standard format for transmitting satellitemodels to a global positioning system receiver.
 38. The apparatus ofclaim 27 wherein the long term satellite tracking data is valid for afirst period of time and the at least a portion of said long termsatellite tracking data is valid for a second period of time, where saidfirst period is longer than said second period.
 39. The apparatus ofclaim 27 wherein said transmitting means comprises: a wirelesscommunications link.
 40. The apparatus of claim 27 wherein saidtransmitting means comprises: a computer network.
 41. The apparatus ofclaim 27 wherein said transmitting means comprises: the Internet.